B.sc. (data Sciences)
Programme Degree Programme in B.sc. (data Sciences)
The school of Sciences and Emerging Technologies of Jagat Guru Nanak Dev Punjab State Open University, Patiala has started Bachelor of Science (Data Science) from the session 2020-21. The university has adopted choice-based credit system which has been introduced by University Grant Commission (UGC). This is a broad-based programme covering disciplinary, interdisciplinary and skill-based subjects. It provides flexibility for the learners to choose the subjects of their interest and also has the opportunity to grow with present digital era. The Bachelor of Science (Data Science) has 132 credits consisting of 4 categories namely Core Courses, Discipline Specific Electives, Ability Enhancement Compulsory Course and Skill Enhancement Courses. This 3-year course is of 6 semesters and each semester consists of 4 papers.
Having passed 10+2 in any Stream or its equivalent examination with Mathematics or Statistics or Computer Science or Economics as one of the Courses in the 10+2 Level from a recognized Board. Learners who have not been taught Mathematics or Statistics or Computer Science or Economics as one of the Courses in the 10+2 Level, they may be admitted in BSc (Data Science) Programme, but they pass a Bridge Course (4-Credits).
Eligibility Criteria of Lateral Entry:
(Lateral Entry) in 2nd Year Having passed 3 Years Diploma from Punjab State Board of Technical Education & Industrial Training, Chandigarh or such examination from any other recognized State Board of Technical Education
| Total Credits: 132 | Min-Duration : 3 Years | Max-Duration : 6 Years | ||||
| Sr. No. | Name of the Course | Course Code | Credit | SM | Syllabus |
|---|---|---|---|---|---|
| Semester 1 | |||||
| 1 | Problem Solving using Computer | BSDB31101T | 4 | - | View |
| 2 | Fundamental of IT | BSDB31102T | 4 | - | View |
| 3 | Introduction Data Science | BSDB31103T | 4 | - | View |
| 4 | Problem Solving using Computer Lab | BSDB31101P | 2 | - | View |
| 5 | Fundamental of IT Lab | BSDB31102P | 2 | - | View |
| 6 | Introduction Data Science Lab | BSDB31103P | 2 | - | View |
| 7 | Effective Communication in English | AE1B31104T | 4 | - | View |
| 8 | Sikh Heritage and Ethos* | SHAE31108T | 0 | - | - |
| Semester 2 | |||||
| 1 | Operating System | BSDB31201T | 4 | - | View |
| 2 | Statistical Foundation | BSDB31202T | 4 | - | View |
| 3 | Introduction to Logic | BSDB31203T | 4 | - | View |
| 4 | Operating System Lab | BSDB31201P | 2 | - | View |
| 5 | Statistical Foundation Lab | BSDB31202P | 2 | - | View |
| 6 | Introduction to Logic Lab | BSDB31203P | 2 | - | View |
| 7 | Environmental Studies | AE2B31204T | 4 | - | View |
| Semester 3 | |||||
| 1 | Database Management Systems | BSDB32301T | 4 | - | View |
| 2 | Data Mining and Visualization | BSDB32302T | 4 | - | View |
| 3 | Data Preparation | BSDB32303T | 4 | - | View |
| 4 | Mathematical Foundation for DS | BSDB32304T | 4 | - | View |
| 5 | Database Management Systems Lab | BSDB32301P | 2 | - | View |
| 6 | Data Mining and Visualization Lab | BSDB32302P | 2 | - | View |
| 7 | Data Preparation Lab | BSDB32303P | 2 | - | View |
| Semester 4 | |||||
| 1 | Computer System Architecture | BSDB32401T | 4 | - | View |
| 2 | Data Communication and Networks | BSDB32402T | 4 | - | View |
| 3 | Machine Learning | BSDB32403T | 4 | - | View |
| 4 | Introduction to Analytics and AI | BSDB32404T | 4 | - | View |
| 5 | Computer System Architecture Lab | BSDB32401P | 2 | - | View |
| 6 | Data Communication and Networks Lab | BSDB32402P | 2 | - | View |
| 7 | Machine Learning Lab | BSDB32403P | 2 | - | View |
| Semester 5 | |||||
| 1 | Introduction to Deep Learning | BSDB33501T | 4 | - | View |
| 2 | Big Data Management | BSDB33502T | 4 | - | View |
| 3 | Software Project Management | BSDB33503T | 4 | - | View |
| 4 | Social Network Analysis | BSDB33504T | 4 | - | View |
| 5 | Introduction to Deep Learning Lab | BSDB33501P | 2 | - | View |
| 6 | Big Data Management Lab | BSDB33502P | 2 | - | View |
| 7 | Software Project Management Lab | BSDB33503P | 2 | - | View |
| Semester 6 | |||||
| 1 | e-Platforms for ML | BSDB33601T | 4 | - | View |
| 2 | Applications of Data Science | BSDB33602T | 4 | - | View |
| 3 | Technical Report Writing | BSDB33603T | 4 | - | View |
| 4 | Applications of Data Science Lab | BSDB33602P | 2 | - | View |
| 5 | Technical Report Writing Lab | BSDB33603P | 2 | - | View |
| 6 | Project | BSDB33604P | 6 | - | View |
Continuous Internal Assessment (30%)
- Two assignments for a 3 or 4-credit course.
- Three for a 6-credit course.
- Pass Percentage : Atleast 30% in each assignment.
- End Semester Exam (70%)
- Pass Percentage: Atleast 30% marks in semester end examinations.
- Atleast 35% marks in both continuous evaluations as well as in semester end examinations separately.
- Overall, at least 40% marks in each course.
Successfully completing Third year of B.Sc (Data Science) Programme and earning 132 credits of Programme, Student will be awarded degree of B.Sc (Data Science).
- Dr. Amitoj Singh
- Associate Professor
- School of Sciences and Emerging Technologies
- amitojsingh{at}psou{dot}ac{dot}in